1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211
|
SUBROUTINE DSTEVD( JOBZ, N, D, E, Z, LDZ, WORK, LWORK, IWORK,
$ LIWORK, INFO )
*
* -- LAPACK driver routine (version 2.0) --
* Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
* Courant Institute, Argonne National Lab, and Rice University
* September 30, 1994
*
* .. Scalar Arguments ..
CHARACTER JOBZ
INTEGER INFO, LDZ, LIWORK, LWORK, N
* ..
* .. Array Arguments ..
INTEGER IWORK( * )
DOUBLE PRECISION D( * ), E( * ), WORK( * ), Z( LDZ, * )
* ..
*
* Purpose
* =======
*
* DSTEVD computes all eigenvalues and, optionally, eigenvectors of a
* real symmetric tridiagonal matrix. If eigenvectors are desired, it
* uses a divide and conquer algorithm.
*
* The divide and conquer algorithm makes very mild assumptions about
* floating point arithmetic. It will work on machines with a guard
* digit in add/subtract, or on those binary machines without guard
* digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
* Cray-2. It could conceivably fail on hexadecimal or decimal machines
* without guard digits, but we know of none.
*
* Arguments
* =========
*
* JOBZ (input) CHARACTER*1
* = 'N': Compute eigenvalues only;
* = 'V': Compute eigenvalues and eigenvectors.
*
* N (input) INTEGER
* The order of the matrix. N >= 0.
*
* D (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the n diagonal elements of the tridiagonal matrix
* A.
* On exit, if INFO = 0, the eigenvalues in ascending order.
*
* E (input/output) DOUBLE PRECISION array, dimension (N)
* On entry, the (n-1) subdiagonal elements of the tridiagonal
* matrix A, stored in elements 1 to N-1 of E; E(N) need not
* be set, but is used by the routine.
* On exit, the contents of E are destroyed.
*
* Z (output) DOUBLE PRECISION array, dimension (LDZ, N)
* If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal
* eigenvectors of the matrix A, with the i-th column of Z
* holding the eigenvector associated with D(i).
* If JOBZ = 'N', then Z is not referenced.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1, and if
* JOBZ = 'V', LDZ >= max(1,N).
*
* WORK (workspace/output) DOUBLE PRECISION array,
* dimension (LWORK)
* On exit, if LWORK > 0, WORK(1) returns the optimal LWORK.
*
* LWORK (input) INTEGER
* The dimension of the array WORK.
* If JOBZ = 'N' or N <= 1 then LWORK must be at least 1.
* If JOBZ = 'V' and N > 1 then LWORK must be at least
* ( 1 + 3*N + 2*N*lg N + 2*N**2 ),
* where lg( N ) = smallest integer k such
* that 2**k >= N.
*
* IWORK (workspace/output) INTEGER array, dimension (LIWORK)
* On exit, if LIWORK > 0, IWORK(1) returns the optimal LIWORK.
*
* LIWORK (input) INTEGER
* The dimension of the array IWORK.
* If JOBZ = 'N' or N <= 1 then LIWORK must be at least 1.
* If JOBZ = 'V' and N > 1 then LIWORK must be at least 2+5*N.
*
* INFO (output) INTEGER
* = 0: successful exit
* < 0: if INFO = -i, the i-th argument had an illegal value
* > 0: if INFO = i, the algorithm failed to converge; i
* off-diagonal elements of E did not converge to zero.
*
* =====================================================================
*
* .. Parameters ..
DOUBLE PRECISION ZERO, ONE, TWO
PARAMETER ( ZERO = 0.0D0, ONE = 1.0D0, TWO = 2.0D0 )
* ..
* .. Local Scalars ..
LOGICAL WANTZ
INTEGER ISCALE, LGN, LIWMIN, LWMIN
DOUBLE PRECISION BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA, SMLNUM,
$ TNRM
* ..
* .. External Functions ..
LOGICAL LSAME
DOUBLE PRECISION DLAMCH, DLANST
EXTERNAL LSAME, DLAMCH, DLANST
* ..
* .. External Subroutines ..
EXTERNAL DSCAL, DSTEDC, DSTERF, XERBLA
* ..
* .. Intrinsic Functions ..
INTRINSIC DBLE, INT, LOG, SQRT
* ..
* .. Executable Statements ..
*
* Test the input parameters.
*
WANTZ = LSAME( JOBZ, 'V' )
*
INFO = 0
LIWMIN = 1
LWMIN = 1
IF( .NOT.( WANTZ .OR. LSAME( JOBZ, 'N' ) ) ) THEN
INFO = -1
ELSE IF( N.LT.0 ) THEN
INFO = -2
ELSE IF( LDZ.LT.1 .OR. ( WANTZ .AND. LDZ.LT.N ) ) THEN
INFO = -6
ELSE IF( N.GT.1 .AND. WANTZ ) THEN
LGN = INT( LOG( DBLE( N ) ) / LOG( TWO ) )
IF( 2**LGN.LT.N )
$ LGN = LGN + 1
IF( 2**LGN.LT.N )
$ LGN = LGN + 1
LWMIN = 1 + 3*N + 2*N*LGN + 2*N**2
LIWMIN = 2 + 5*N
IF( LWORK.LT.LWMIN ) THEN
INFO = -8
ELSE IF( LIWORK.LT.LIWMIN ) THEN
INFO = -10
END IF
ELSE IF( LWORK.LT.1 ) THEN
INFO = -8
ELSE IF( LIWORK.LT.1 ) THEN
INFO = -10
END IF
*
IF( INFO.NE.0 ) THEN
CALL XERBLA( 'DSTEVD', -INFO )
GO TO 10
END IF
*
* Quick return if possible
*
IF( N.EQ.0 )
$ GO TO 10
*
IF( N.EQ.1 ) THEN
IF( WANTZ )
$ Z( 1, 1 ) = ONE
GO TO 10
END IF
*
* Get machine constants.
*
SAFMIN = DLAMCH( 'Safe minimum' )
EPS = DLAMCH( 'Precision' )
SMLNUM = SAFMIN / EPS
BIGNUM = ONE / SMLNUM
RMIN = SQRT( SMLNUM )
RMAX = SQRT( BIGNUM )
*
* Scale matrix to allowable range, if necessary.
*
ISCALE = 0
TNRM = DLANST( 'M', N, D, E )
IF( TNRM.GT.ZERO .AND. TNRM.LT.RMIN ) THEN
ISCALE = 1
SIGMA = RMIN / TNRM
ELSE IF( TNRM.GT.RMAX ) THEN
ISCALE = 1
SIGMA = RMAX / TNRM
END IF
IF( ISCALE.EQ.1 ) THEN
CALL DSCAL( N, SIGMA, D, 1 )
CALL DSCAL( N-1, SIGMA, E( 1 ), 1 )
END IF
*
* For eigenvalues only, call DSTERF. For eigenvalues and
* eigenvectors, call DSTEDC.
*
IF( .NOT.WANTZ ) THEN
CALL DSTERF( N, D, E, INFO )
ELSE
CALL DSTEDC( 'I', N, D, E, Z, LDZ, WORK, LWORK, IWORK, LIWORK,
$ INFO )
END IF
*
* If matrix was scaled, then rescale eigenvalues appropriately.
*
IF( ISCALE.EQ.1 )
$ CALL DSCAL( N, ONE / SIGMA, D, 1 )
*
10 CONTINUE
IF( LWORK.GT.0 )
$ WORK( 1 ) = LWMIN
IF( LIWORK.GT.0 )
$ IWORK( 1 ) = LIWMIN
RETURN
*
* End of DSTEVD
*
END
|